Theoretical and Applied Climatology

, Volume 44, Issue 1, pp 9–24 | Cite as

Diurnal variability of the Earth Radiation Budget: Sampling requirements, time integration aspects and error estimates for the Earth Radiation Budget Experiment (ERBE)

  • M. Rieland
  • E. Raschke


The diurnal variation of the Earth Radiation Budget and its components require for sparsely temporal sampling a high amount of modeling for the derivation of precise daily averages. In the present study the time integration errors of the regional monthly averages of the Earth Radiation Budget Experiment (Barkstrom, 1984) are estimated for April 1985. For this error assessment we made use of data of the European geostationary satellite Meteosat 2 which narrowbanded measurements have been converted to reasonable estimates of broad-band radiation fluxes. Based on this data set the measurements of the ERBE satellites, ERBS, NOAA 9, and NOAA 10 are simulated. For the time integration the ERBE time integration models are used.

The mean error for the regional monthly average of the net radiation flux varies between — 3 and + 5 W/m2 for the combination of all three satellites. The largest contribution to this uncertainty is given by the time integration of the shortwave fluxes. A new approach for the time integration procedure is presented which is based on the Maximum Entropy spectral analysis of temporal high resolution data sets as provided by geostationary satellites.

This study closes with the estimation of the final error for ERBE regional monthly averages of the net radiation flux, which includes the uncertainties of the instruments, the inversion process and the time integration process. These errors lie between 11.1 W/m2 for single NOAA 9 products and 7.8 W/m2 for the combination of all three satellites. With that the Earth Radiation Budget Experiment fulfills the required accuracy.


Time Integration Inversion Process Geostationary Satellite Integration Error Earth Radiation 
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  1. Barkstrom, B. R., 1984: The Earth Radiation Budget Experiment (ERBE).Bull. Amer. Meteor. Soc. 65, 1170.Google Scholar
  2. Barkstrom, B. R., Smith, G. L., 1986: The Earth Radiation Budget Experiment: Science and Implementation.Rev. Geoph.,24, (2), May 1986.Google Scholar
  3. Brooks, D. R., Minnis, P., 1984: Simulation of the Earth's Monthly Average Regional Radiation Balance derived from satellite measurements,J. Climate Appl. Meteor. 23, 392–403.Google Scholar
  4. Brooks, D. R., Harrison, E. F., Minnis, P., Suttles, J. T., 1986: Development of Algorithms for understanding the temporal and spatial variability of the Earth's Radiation Balance.Rev. Geoph. 24, (2), 422–438.Google Scholar
  5. Diekmann, F. J., 1988: Fehler in der Szenenerkennung aus Satellitendaten — Auswirkungen auf die Bestimmung von Strahlungshaushaltsparametern, Mitteilungen Inst. f. Geoph. u. Met. Universität Köln, No 59.Google Scholar
  6. Diekmann, F. J., Smith, G. L., 1989: Investigation of Scene Identification Algorithms for Radiation Budget Measurements.J. Geophys. Res. 94, (D3), 3395–3412.Google Scholar
  7. England, C., Hunt, G. E., 1984: Studies of the spatial and temporal errors in satellite estimates of the earth's radiation budget.Tellus, Ser. B 36, 303–316.Google Scholar
  8. Gube, M., 1982: Computation of the earth's radiation budget from spectral radiance measurements of the satellite Meteosat, ESA STR-210, ESA, Darmstadt.Google Scholar
  9. Harrison, E. F., Minnis, P., Gibson, G. G., 1983: Orbital and cloud cover sampling analysis for multisatellite earth radiation budget experiments.J. Spacecraft and Rockets 20, (5), 491–495.Google Scholar
  10. Hartmann, D. L., Ramanathan, V., Berroir, A., Hunt, G. E., 1986: Earth Radiation Budget Data and Climate Research.Rev. Geophys. 24, 429–468.Google Scholar
  11. Jaynes, E. T., 1982: On the rationale of maximum entropy methods.Proc. of IEEE 70, (9), 939–952.Google Scholar
  12. Kandel, R. S., Duvel, J. P., 1987: Diurnal variation of the Earth Radiation Budget Components above Africa and the neighboring Atlantic Ocean; Changes between 1983 and 1985, estimated from Meteosat observations adjusted to ERBS data.Adv. Space Res. 7, (3), 3179–3186.Google Scholar
  13. Kandel, R. S., Cheruy, F., Duvel, J. P., 1989: Estimating the outgoing longwave radiation from the Meteosat infrared window and water vapor bands. Lenoble, J., Geleyn, J.-F., (eds) Proc. IRS 1988, Lille, Deepak Publ., 221–224.Google Scholar
  14. Kandel, R. S., Monge, J. L., Viollier, M., Pakhomov, L. A., 1989: The Franco — Soviet SCARAB Project, Rev. Papers a. Abstracts IAMAP 89, 31.7.–12.8.1989, University of Reading, UK.Google Scholar
  15. Minnis, P., Harrison, E. F., 1984: Diurnal variability of regional cloud and clear-sky radiative parameters derived from GOES data.J. Climate Appl. Meteor. 23, 993–1051; Part I: Analysis Method, Part II: November 1978 cloud distributions, Part III: November 1978 radiative parameters.Google Scholar
  16. NOAA Techn. Report NESDIS 41, 1988: Report of the Earth Radiation Budget Requirements Review — 1987, Rosslyn, Va., 30 March–3 April 1987. Stowe, L.L., (ed) Washington D.C.Google Scholar
  17. Potter, G. L., Cess, R. D., Minnis, P., Harrison, E. F., Ramanathan, V., 1988: Diurnal variability of the planetary albedo: an appraisal with satellite measurements and general circulation models.J. Clim. 1, 233–239.Google Scholar
  18. Preuß, H. J., Raschke, E., Daniel, M., 1984: Studies of the sampling of space-borne radiation budget measurements.Meteorol. Rdsch. 37, 52.Google Scholar
  19. Rieland, M., 1989: Diurnal variation of rath radiation budget components derived from Meteosat data, Lenoble, J., Geleyn, J.-F., (eds) Proc. IRS 1988, Lille, Deepak Publ., 217–220.Google Scholar
  20. Rieland, M., 1989: Stichprobenanalysen des Tagesganges der planetaren Strahlungsbilanz. Mitteilungen Inst. f. Geoph. u. Met. Universität Köln, No 68.Google Scholar
  21. Schiffer, R. A., Rossow, W. B., 1983: The International Satellite Cloud Climatology Project (ISCCP): The first project of the World Climate Research Programme.Bull. Amer. Meteor. Soc. 64, 779–784.Google Scholar
  22. Schmetz, J., Liu, Q., 1989: Outgoing longwave radiation and its diurnal variation at regional scales derived from Meteosat,J. Geophys. Res., May 1988.Google Scholar
  23. Slingo, A., 1987: User requirements for Earth Radiation Budget Data. Overview presentation for the Earth Radiation Budget Requirements Review, Rosslyn, Va., 30 March–3 April 1987.Google Scholar
  24. Smith, G. L., Green, R. N., Raschke, E., Avis, L. A., Suttles, J. T., Wielicki, B. A., Davies, R., 1986: Inversion Methods for Satellite Studies of the Earth's Radiation Budget: Development of Algorithms for the ERBE Mission.Rev. Geoph. 24, (2), 407–421.Google Scholar
  25. Suttles, J. T. et al.: Angular Radiation Models for Earth Atmosphere Vol I: SW Radiation Vol II: LW Radiation, NASA Reference Publ. 1184 July 1985 (VOL I), April 1989 (VOL II).Google Scholar
  26. Taylor, V. R., Stowe, L. L., 1984: Reflectance characteristics of uniform earth and cloud surfaces derived from NIMBUS 7 ERB.J. Geophys. Res. 89 (D4), 4987–4996.Google Scholar
  27. Ulrych, T. J., Bishop, T. N., 1975: Maximum Entropy Spectral Analysis and Autoregressive Decomposition.Rev. Geophys. Space Phys. 13, (1), 183–200.Google Scholar
  28. Vonder Haar, T. H., Suomi, V. E., 1971: Measurements of the earth's radiation budget from satellites during a fiveyear period.J. Atmos. Sci. 28 (3), 305–314.Google Scholar
  29. Wiegner, M., Raschke, E., 1987: Planetary Radiation Budget over North Africa from satellite data,Theor. Appl. Clim. 38, 24–36.Google Scholar
  30. Wielicki, B. A., Barkstrom, B. R., 1989: “Clouds and the Earth's Radiant Energy System (CERES): The Next Generation of Radiation Measurements”, Rev. Papers a. Abstracts IAMAP 89, 31.7.–12.8. 1989, University of Reading, U.K.Google Scholar

Copyright information

© Springer-Verlag 1991

Authors and Affiliations

  • M. Rieland
    • 1
  • E. Raschke
    • 2
  1. 1.Meteorologisches Institut der Universität HamburgHamburg 13Germany
  2. 2.Institut für Physik, GKSS-ForschungszentrumGeesthachtGermany

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